NFkB is an inducible transcription factor that is activated in response to stress, cytokines and bacterial and viral pathogens, and is a major regulator of immune responses. The NFkB regulatory network processes signals that originate at a variety of cell membrane receptors to control the transcription of genes involved in immune and inflammatory responses, cell proliferation and survival. NFkB signaling has been linked to a number of human inflammatory diseases, such as arthritis and asthma, and because its activity is often up- regulated in tumors, NFkB signaling is actively being pursued as a target for cancer therapies. A detailed understanding of the signaling pathways that culminate in NFkB activation will be crucial for the discovery of effective NFkB inhibitors. To this end, this project will develop and experimentally validate computational models with predictive capabilities that can be used to understand the complexities of NFkB signaling in mammalian cells. Each aim will investigate a particular aspect of NFkB signaling through a combination of modeling and quantitative single-cell experiments performed in controlled microfluidic environments. Specifically, the first aim will develop a stochastic delay-based computational model of NFkB dynamics driven by transient TNF signals. For this, novel cell lines will be created that allow IKK and NFkB expression to be tracked in real time by fluorescence microscopy. Modeling will be used to predict the network response to various driving conditions and mutations in network architecture. The second aim will focus on the role of the IKK regulatory cycle in amplifying or filtering fluctuations in signals emanating from receptors. The rate of IKK turnover within the cycle will be varied to study the propagation of upstream fluctuations into the core of the NFkB module. The third aim will address the role of two parallel pathways (MyD88 and TRIF) initiated by pathogen-derived lipopolysaccharide (LPS) signals. Experiments involving either carefully controlled pulses of external LPS or invasive E. coli will be used in conjunction with mathematical modeling to characterize the dynamics and variability of the LPS-NFkB pathways. In the fourth aim, the role of cell-to-cell signaling in generating NFkB-mediated responses will be addressed by examining autocrine and paracrine TNF signaling. The successful completion of this project will result not only in a predictive computational model for NFkB signaling but also in insights into how this central regulatory network processes information in response to stimulation, inhibition, and drug modulation.